Data analysis and learning: an experimental study of data modeling tools
International Journal of Man-Machine Studies
Requirements specification: learning object, process, and data methodologies
Communications of the ACM
Intelligent database design using the unifying semantic model
Information and Management
The Unified Modeling Language reference manual
The Unified Modeling Language reference manual
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
An ontological analysis of the relationship construct in conceptual modeling
ACM Transactions on Database Systems (TODS)
Understanding relationships with attributes in entity-relationship diagrams
ICIS '99 Proceedings of the 20th international conference on Information Systems
Evaluating ontological decisions with OntoClean
Communications of the ACM - Ontology: different ways of representing the same concept
Multimedia Learning
Should Optional Properties Be Used in Conceptual Modelling? A Theory and Three Empirical Tests
Information Systems Research
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management
The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management
Towards the semantic web: knowledge representation in a dynamic, distributed environment
Towards the semantic web: knowledge representation in a dynamic, distributed environment
Ontological Engineering
QuizRDF: Search Technology for the Semantic Web
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
Modeling cognitive processes in information seeking: from popper to pask
Journal of the American Society for Information Science and Technology - Special issue: Part II: Information seeking research
Ontology based object-oriented domain modelling: fundamental concepts
Requirements Engineering
Complexity and clarity in conceptual modeling: comparison of mandatory and optional properties
Data & Knowledge Engineering - Special issue: Quality in conceptual modeling
Data & Knowledge Engineering - Special issue: Quality in conceptual modeling
Cognitive fit in requirements modeling: a study of object and process methodologies
Journal of Management Information Systems - Special section: Strategic and competitive information systems
Towards defining dimensions of knowledge systems quality
Expert Systems with Applications: An International Journal
The double role of ontologies in information science research: Research Articles
Journal of the American Society for Information Science and Technology
Information Systems Research
Understanding Conceptual Schemas: Exploring the Role of Application and IS Domain Knowledge
Information Systems Research
Visualization of web spaces: state of the art and future directions
ACM SIGMIS Database
Knowledge Representation with Ontologies: The Present and Future
IEEE Intelligent Systems
Guideline based evaluation and verbalization of OWL class and property labels
Data & Knowledge Engineering
Profiting from Knowledge Management: The Impact of Time and Experience
Information Systems Research
The nature of theory in information systems
MIS Quarterly
Using Ontology Languages for Conceptual Modeling
Journal of Database Management
Scope of ontological annotation in e-commerce
International Journal of Business Information Systems
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Organizations often provide workers with knowledge management systems to help them obtain knowledge they need. A significant constraint on the effectiveness of such systems is that they assume workers know what knowledge they need (they know what they don't know) when, in fact, they often do not know what knowledge they need (they don't know what they don't know). A way to overcome this problem is to use visual ontologies to help users learn relevant concepts and relationships in the knowledge domain, enabling them to search the knowledge base in a more educated manner. However, no guidelines exist for designing such ontologies. To fill this gap, we draw on theories of philosophical ontology and cognition to propose guidelines for designing visual ontologies for knowledge identification. We conducted three experiments to compare the effectiveness of guided ontologies, visual ontologies that followed our guidelines, to unguided ontologies, visual ontologies that violated our guidelines. We found that subjects performed considerably better with the guided ontologies, and that subjects could perceive the benefits of using guided ontologies, at least in some circumstances. On the basis of these results, we conclude that the way visual ontologies are presented makes a difference in knowledge identification and that theories of philosophical ontology and cognition can guide the construction of more effective visual representations. Furthermore, we propose that the principles we used to create the guided visual ontologies can be generalized for other cases where visual models are used to inform users about application domains.